关键词: 花朵授粉算法, 天牛须搜索, 变异策略

Abstract: Aiming at the slow convergence rate and low optimization accuracy of flower pollination algorithm, a new Beetle Antenna Search Flower Pollination Algorithm（BASFPA） is proposed. Firstly, the algorithm uses the beetle antennae search in global search to improve the convergence rate of algorithm, then it uses perturbation evolution in local search to help the algorithm jump out of local optimal. Six commonly used optimization functions are used in experiment to test BASFPA, the result shows that the BASFPA algorithm has a significant improvement of convergence speed and optimization accuracy in low-dimensional and high-dimensional optimization, and the number of iterations required to achieve the same accuracy is less than other algorithms, it is proved that the improvement of this algorithm is reasonable.

Key words: flower pollination algorithm, beetle antennae search, mutation strategy